Project description:MOLECULAR PROFILING IMPROVES DIAGNOSES OF REJECTION AND INFECTION IN TRANSPLANTED ORGANS. The monitoring of transplanted hearts is currently based on histological evaluation of endomyocardial biopsies, a method that is fairly insensitive and that does not always accurately discriminate between rejection and infection in the heart. Accurate diagnosis of rejection and infection is absolutely crucial, however, as the respective treatments are completely different. Using microarrays we analyzed gene expression in 76 cardiac biopsies from 40 heart recipients undergoing rejection, no rejection, or T. cruzi infection. We found a set of 98 genes whose expression patterns were typical of acute rejection, and 87 genes that discriminated between rejection and T. cruzi infection. These sets revealed acute rejection episodes up to two weeks earlier, and trypanosome infection up to two months earlier than did histological evaluation. When applied to raw data from other institutions, the two sets of predictive genes were also able to accurately pinpoint acute rejection of lung and kidney transplants, as well as bacterial infections in kidneys. In addition to their usefulness as diagnostic tools, the data suggest that there are similarities in the biology of the processes involved in rejection of different grafts and also in the tissue responses to pathogens as diverse as bacteria and protozoa. Keywords: disease state analysis
Project description:The brain-computer interface (BCI) has been investigated as a form of communication tool between the brain and external devices. BCIs have been extended beyond communication and control over the years. The 2020 international BCI competition aimed to provide high-quality neuroscientific data for open access that could be used to evaluate the current degree of technical advances in BCI. Although there are a variety of remaining challenges for future BCI advances, we discuss some of more recent application directions: (i) few-shot EEG learning, (ii) micro-sleep detection (iii) imagined speech decoding, (iv) cross-session classification, and (v) EEG(+ear-EEG) detection in an ambulatory environment. Not only did scientists from the BCI field compete, but scholars with a broad variety of backgrounds and nationalities participated in the competition to address these challenges. Each dataset was prepared and separated into three data that were released to the competitors in the form of training and validation sets followed by a test set. Remarkable BCI advances were identified through the 2020 competition and indicated some trends of interest to BCI researchers.
Project description:Multiple sinks competition is investigated for a walker diffusing on directed complex networks. The asymmetry of the imposed spatial support makes the system non transitive. As a consequence, it is always possible to identify a suitable location for the second absorbing sink that screens at most the flux of agents directed against the first trap, whose position has been preliminarily assigned. The degree of mutual competition between pairs of nodes is analytically quantified through apt indicators that build on the topological characteristics of the hosting graph. Moreover, the positioning of the second trap can be chosen so as to minimize, at the same time, the probability of being in turn shaded by a thirdly added trap. Supervised placing of absorbing traps on a asymmetric disordered and complex graph is hence possible, as follows a robust optimization protocol. This latter is here discussed and successfully tested against synthetic data.
Project description:This is a test study for the purpose of submitters wishing to test the EGA submission procedure. All objects, such as DAC and datasets, linked to this study can also be considered to be for testing purposes.
Project description:We created earlier a large machine-readable database of 10,000 chemicals and 800,000 associated studies by natural language processing of the public parts of Registration, Evaluation, Authorisation and Restriction of Chemicals (REACH) registrations until December 2014. This database was used to assess the reproducibility of the six most frequently used Organisation for Economic Co-operation and Development (OECD) guideline tests. These tests consume 55% of all animals in safety testing in Europe, i.e. about 600,000 animals. With 350-750 chemicals with multiple results per test, reproducibility (balanced accuracy) was 81% and 69% of toxic substances were found again in a repeat experiment (sensitivity 69%). Inspired by the increasingly used read-across approach, we created a new type of QSAR, which is based on similarity of chemicals and not on chemical descriptors. A landscape of the chemical universe using 10 million structures was calculated, when based on Tanimoto indices similar chemicals are close and dissimilar chemicals far from each other. This allows placing any chemical of interest into the map and evaluating the information available for surrounding chemicals. In a data fusion approach, in which 74 different properties were taken into consideration, machine learning (random forest) allowed a fivefold cross-validation for 190,000 (non-) hazard labels of chemicals for which nine hazards were predicted. The balanced accuracy of this approach was 87% with a sensitivity of 89%. Each prediction comes with a certainty measure based on the homogeneity of data and distance of neighbours. Ongoing developments and future opportunities are discussed.
Project description:The objective of this paper is to describe general approaches of diagnostic test accuracy (DTA) that are available for the quantitative synthesis of data using R software. We conduct a DTA that summarizes statistics for univariate analysis and bivariate analysis. The package commands of R software were "metaprop" and "metabin" for sensitivity, specificity, and diagnostic odds ratio; forest for forest plot; reitsma of "mada" for a summarized receiver-operating characteristic (ROC) curve; and "metareg" for meta-regression analysis. The estimated total effect sizes, test for heterogeneity and moderator effect, and a summarized ROC curve are reported using R software. In particular, we focus on how to calculate the effect sizes of target studies in DTA. This study focuses on the practical methods of DTA rather than theoretical concepts for researchers whose fields of study were non-statistics related. By performing this study, we hope that many researchers will use R software to determine the DTA more easily, and that there will be greater interest in related research.
Project description:BackgroundDrug-Resistant Tuberculosis (DR-TB) is one of the major challenges to TB control.Design and methodsThis was a blinded, laboratory-based cross-sectional study using sputum samples or culture isolates. Samples were from patients with rifampicin-resistant-TB and/or with high risk for isoniazid (INH) resistance and/or 2nd line fluoroquinolones (FQ) and injectable agents (IAs). The diagnostic accuracy of the Xpert® MTB/XDR test was compared to MGIT960 and the Hain Genotype® MTBDRplus and MDRsl assays (LPA) as reference DST methods. Factors for laboratory uptake of the Xpert® MTB/XDR test were also evaluated.ResultsOf the 100 stored sputum samples included in this study, 65/99 (65.6%) were resistant to INH, 5/100 (5.0%) were resistant to FQ and none were resistant to IAs using MGIT960. The sensitivity and specificity, n (%; 95% Confidence Interval, CI) of Xpert® MTB/XDR test for; INH was 58 (89.2; 79.1-95.5) and 30 (88.2; 72.5-96.6) and for FQ; 4 (80.0; 28.3-99.4) and 95 (100; 96.2-100), respectively. Using LPA as a reference standard, a total of 52/98 (53.1%) were resistant to INH, 3/100 (3.0%) to FQ, and none to IA. The sensitivity and specificity, n (%; 95%CI) of Xpert® MTB/XDR test compared to LPA for; INH was 50 (96.1; 86.7-99.5) and 34 (74.0; 58.8-85.7) for FQ 3 (100; 29.2-100) and 96 (99.0; 94.3-99.9) respectively. The factors for laboratory uptake and roll-out of the Xpert® MTB/XDR test included: no training needed for technicians with, and one day for those without, previous Xpert-ultra experience, recording and reporting needs were not different from those of Xpert-ultra, the error rate was 4/100 (4%), one (1%) indeterminate rate and test turn-around-time were 1hr/45 minutes.ConclusionThere is high sensitivity and specificity of Xpert® MTB/XDR test for isoniazid and fluoroquinolones. There are acceptable Xpert® MTB/XDR test attributes for the test uptake and roll-out.
Project description:Competitive diversification, that is, when increasing intraspecific competition promotes population niche expansion, is commonly invoked in evolutionary studies and currently plays a central role in how we conceptualize the process of adaptive diversification. Despite the frequency with which this idea is cited, the empirical evidence for the process is somewhat limited, and the findings of these studies have yet to be weighed objectively through synthesis. Here, we sought to fill this gap by reviewing the existing literature and collecting the data necessary to assess the evidence for competition as a diversifying force. Additionally, we sought to test a more recent hypothesis, which suggests that competition can act to both promote and inhibit dietary diversification depending on the degree to which a consumer depletes its resources. The surprising result of this synthesis was that increasing competition did not have a mean positive effect on population-level diet breadth or the degree of individual specialization. Instead, we found that increasing intraspecific competition had a restricting effect on population-level diet breadth in as many cases as it had a diversifying effect. This wide disparity in the effect of competition on consumer diet variation was negatively related to a metric for consumer resource depletion. Altogether, these findings call into question a long-standing assumption of basic evolutionary models and lend some support to recent theoretical predictions. Specifically, these findings support the idea that competition is primarily diversifying for species with a small effect (per unit biomass) on their resources and that resource depletion limits the diversifying effect of competition for consumers with larger ecological effects.